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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Sistemasi: Jurnal Sistem Informasi Jurnal Informatika Jurnal Pilar Nusa Mandiri Jurnal Manajemen Informatika Jurnal Teknologi dan Informasi Jurnal Sistem Komputer & Kecerdasan Buatan Abdimasku : Jurnal Pengabdian Masyarakat Jurnal AbdiMas Nusa Mandiri
Nawawi, Hendri Mahmud
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Industrial & Manufacturing Engineering Mathematics Physics Social Sciences Other

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Journal : Jurnal Pilar Nusa Mandiri

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KOMPARASI ALGORITMA NEURAL NETWORK DAN NAÏVE BAYES UNTUK MEMPREDIKSI PENYAKIT JANTUNG Nawawi, Hendri Mahmud; Purnama, Jajang Jaya; Hikmah, Agung Baitul
Jurnal Pilar Nusa Mandiri Vol 15 No 2 (2019): Pilar Nusa Mandiri : Journal of Computing and Information System Periode Septemb
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (934.982 KB) | DOI: 10.33480/pilar.v15i2.669

Abstract

Heart disease is one of the types of deadly diseases whose treatment must be dealt with as soon as possible because it can occur suddenly to the sufferer. Factors of heart disease that are recognized based on the condition of the body of a sufferer need to be known from an early age so that the risk of possible instant attacks can be minimized or can be overcome in various ways such as a healthy lifestyle and regular exercise that can regulate heart health in the body. By looking at the condition of a person's body based on sex, blood pressure, age, whether or not a smoker and some indicators that become a person's characteristics of heart disease are described in a study using the Neural Network and Naïve Bayes algorithm with the aim of comparing the level of accuracy to attributes influential to predict heart disease, so the results of this study can be used as a reference to predict whether a person has heart disease or not.
IMAGE BACKGROUND PROCESSING FOR COMPARING ACCURACY VALUES OF OCR PERFORMANCE Kholifah, Desiana Nur; Nawawi, Hendri Mahmud; Thira, Indra Jiwana
Jurnal Pilar Nusa Mandiri Vol 16 No 1 (2020): Pilar Nusa Mandiri : Journal of Computing and Information System Publishing Peri
Publisher : LPPM Universitas Nusa Mandiri

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1274.786 KB) | DOI: 10.33480/pilar.v16i1.1076

Abstract

Optical Character Recognition (OCR) is an application used to process digital text images into text. Many documents that have a background in the form of images in the visual context of the background image increase the security of documents that state authenticity, but the background image causes difficulties with OCR performance because it makes it difficult for OCR to recognize characters overwritten by background images. By removing background images can maximize OCR performance compared to document images that are still background. Using the thresholding method to eliminate background images and look for recall values, precision, and character recognition rates to determine the performance value of OCR that is used as the object of research. From eliminating the background image with thresholding, an increase in performance on the three types of OCR is used as the object of research.
Co-Authors Agung Baitul Hikmah Agung Sasongko Agustiani, Sarifah Ali Mustopa, Ali ANI OKTARINI SARI, ANI OKTARINI Eri Bayu Pratama, Eri Bayu Gata, Windu Jajang Jaya Purnama Junianto, Rahmad Kahfi, Ahmad Hafidzul Kholifah, Desiana Nur Nugraha, Fitra Septia Ridwansyah Ridwansyah Risnandar, Risnandar S, M. Rangga Ramadhan Sarwono Sarwono Siti Khotimatul Wildah Susy Rosyida Thira, Indra Jiwana